Research Publications

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Author: search.filters.author.Baral, ArijitSubject: search.filters.subject.Conductivity

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    Investigation related to performance parameter estimation of power transformer insulation using interfacial charge
    (IEEE, 2020-08-04) Mishra, Deepak; Verma, R.; Baral, Arijit; Chakravorti, Sivaji
    In the present paper, geometric capacitance is used as a normalization factor instead of DC insulation resistance. The results suggest geometric capacitance is more efficient in reducing geometry effect on the DC-trapped charge. The influence of normalizing deep charge using DC insulation resistance and geometric capacitance and their effect on estimating various insulation sensitive parameters are compared in this paper.
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    Use of interfacial charge for diagnosis and activation energy prediction of oil-paper insulation used in power transformer
    (IEEE, 2019-01-13) Mishra, Deepak; Dutta, Saurabh; Baral, Arijit; Haque, Nasirul; Chakravorti, Sivaji
    Activation energy is popularly used for the estimation of remaining life of transformer insulation. It is defined as the average rate of all reactions that happen with cellulose. Existing literature shows that the activation energy of oil-paper insulation can be obtained from polarization depolarization current (PDC) and return voltage measurement (RVM) data that are measured at a specific temperature. It is practically difficult to ensure the same measurement temperature for both PDC and RVM data. On the other hand, PDC data and its analysis get influenced by de-trapping current. This de-trapping current is generated by ionic charge carriers that get freed from trap sites during PDC measurement process. Formation of these trap sites is related to physical, chemical reactions that happen at oil-paper interface. This paper proposes a methodology which uses de-trapped charge, dislodged from deep and shallow traps, to assess insulation condition and for the prediction of activation energy. Thus, eliminating the need of RVM data. The proposed method is tested using data collected from various real-life in-service transformers.